3D organoid models are becoming increasingly important in biological research and drug discovery. However, their use remains difficult to standardize because the workflow is complex, highly sensitive to error, and requires extensive training to maintain cell cultures.
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To address the limitations of labor-intensive 3D cell culture techniques, Molecular Devices developed the CellXpress.ai® Automated Cell Culture System, enabling fully automated organoid culture.
The CellXpress.ai system consists of four basic components: a liquid handler, an incubator, an imager, and integrated AI-powered software that automates sophisticated protocol processing and scheduling based on image analysis results.
Automating 3D organoid culture manufacturing involves plating organoid domes, changing fluid, imaging organoids, and passing them around. Molecular Devices automated workflows for three types of organoids: mouse intestinal organoids, human intestinal organoids, and patient-derived colorectal carcinoma organoids.
3D cultures were started by seeding organoids into Matrigel domes in a 24-well plate configuration. Media swaps were performed automatically every 24 hours utilizing the liquid handler component of the CellXpress.ai system. Organoids were automatically passed through using liquid handling and an external centrifuge.
Passaging was timed according to organoid development and phenotype. Scientists assessed mature phenotypes and created machine-learning procedures for identifying and counting mature organoids.
The software then made automated decisions about triggering passaging based on the picture analysis results. Organoid cultures were photographed every 12 hours using transmitted light at 4X magnification.
Following this, AI-based image analysis enabled the recognition of organoid objects in transmitted light, followed by the extraction of numerous phenotypic readouts, including shape, intensity, and texture.
Organoids were classed as "mature phenotype" or "immature phenotype" using a custom-trained machine learning model that was tuned for each of the three organoid kinds.
Through image analysis, the AI model classified organoid morphologies and initiated the automatic passaging process when organoids in the culture matured and required passage. Molecular Devices developed several AI-based protocols and presented findings on the automated cultivation of three distinct organoid types.
Passaging processes were triggered automatically based on a user-defined percentage and number of mature organoids in the culture (usually 40-50 %). The AI-based classification helped to automate 3D culture and organoid expansion, resulting in a fully automated walkaway system for organoid culture.
Acknowledgments
Produced from materials originally authored by Oksana Sirenko, Krishna Macha, Zhisong Tong, Auguste Kersulyte, Astrid Michlmayr, Misha Bashkurov, Marco Lindner, and Felix Spira from Molecular Devices.
About Molecular Devices UK Ltd 
Molecular Devices is one of the world’s leading providers of high-performance bioanalytical measurement systems, software, and consumables for life science research, pharmaceutical, and biotherapeutic development. Included within a broad product portfolio are platforms for high-throughput screening, genomic and cellular analysis, colony selection, and microplate detection. These leading-edge products enable scientists to improve productivity and effectiveness, ultimately accelerating research and the discovery of new therapeutics. Molecular Devices is committed to the continual development of innovative solutions for life science applications. The company is headquartered in Silicon Valley, California, with offices around the globe. For more information, please visit www.moleculardevices.com.
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